The book provides an encompassing overview of all aspects relating to the sharing economy paradigm in different fields of study, and shows the ongoing research efforts in filling previously identified gaps in understanding in this area. Control and optimization analytics for the sharing economy explores bespoke analytics, tools, and business models that can be used to help design collaborative consumption services (the shared economy). It provides case studies of collaborative consumption in the areas of energy and mobility. The contributors review successful examples of sharing systems, and explore the theory for designing effective and stable shared-economy models. They discuss recent innovations in and uses of shared economy models in niche areas, such as energy and mobility. Readers learn the scientific challenging issues associated with the realization of a sharing economy. Conceptual and practical matters are examined, and the state-of-the-art tools and techniques to address such applications are explained. The contributors also show readers how topical problems in engineering, such as energy consumption in power grids, or bike sharing in transportation networks, can be formulated and solved from a general collaborative consumption perspective. Since the book takes a mathematical perspective to the topic, researchers in business, computer science, optimization and control find it useful. Practitioners also use the book as a point of reference, as it explores and investigates the analytics behind economy sharing.

What are the relations between the shape of a system of cities and that of fish school? Which events should happen in a cell in order that it participates to one of the finger of our hands? How to interpret the shape of a sand dune? This collective book written for the non-specialist addresses these questions and more generally, the fundamental issue of the emergence of forms and patterns in physical and living systems. It is a single book gathering the different aspects of morphogenesis and approaches developed in different disciplines on shape and pattern formation. Relying on the seminal works of D'Arcy Thompson, Alan Turing and Rene Thom, it confronts major examples like plant growth and shape, intra-cellular organization, evolution of living forms or motifs generated by crystals. A book essential to understand universal principles at work in the shapes and patterns surrounding us but also to avoid spurious analogies.

The nucleus of this volume consists of a number of papers presented at the Advanced Research Workshop on liThe Impact of New Information Technologies on Library Management, Resources and Cooperation" , held in Luxembourg fran 19-23 November 1984. The oorkshop was a joint effort of four international organisations. The Scientific Affairs Division of the North .Atlantic Treaty Organization, through a personal canmitment and interest expressed by Dr. H. Durand, Assistant Secretary General for Scientific Affairs, was the first and major sponsor acting as a catalyst in enabling the Workshop to take place. Through its support for travel and subsistence costs of some of the North American participants, the Workshop could become a platfo~in for the exchange of ideas between parties concerned with information handling and transmission and information policy in Western Europe and North America. The Directorate General for Information Market and Innovation of the Canmission of the European Communities hosted the Vlorkshop in its facilities - the Jean l'bnnet Building in Luxembourg - also providing for simultaneous translation in the main languages of the European Community. Moreover, the Canmission generously funded the participation of key participants fran Community countries and provided participants with ample info~ination on existing Community programmes related to electronic publications, electronic transmission of documents, copyright problems, problems of standards, telecanmunication, and so on. 'I'he Council of Europe supported attendance fran Sweden, Austria and Spain. And lastly, the European Cultural Foundation organised the event on behalf of all these organisa tions.

This book bridges the current gap between the theory of symmetry-based dynamics and its application to model and analyze complex systems. As an alternative approach, the authors use the symmetry of the system directly to formulate the appropriate models, and also to analyze the dynamics. Complex systems with symmetry arise in a wide variety of fields, including communication networks, molecular dynamics, manufacturing businesses, ecosystems, underwater vehicle dynamics, celestial and spacecraft dynamics and continuum mechanics. A general approach for their analysis has been to derive a detailed model of their individual parts, connect the parts and note that the system contains some sort of symmetry, then attempt to exploit this symmetry in order to simplify numerical computations. This approach can result in highly complicated models that are difficult to analyze even numerically. The alternative approach, while nonstandard, is not entirely new among the mathematics community. However, there is much less familiarity with the techniques of symmetry-breaking bifurcation, as they apply to the engineering, design and fabrication, of complex systems, in particular, nonlinear sensor devices with special emphasis on the conceptualization and development of new technologies of magnetic sensors such as fluxgate magnetometers and SQUID (Superconducting Quantum Interference Devices), E-- (electric-field) sensors, and communication and navigation systems that require multiple frequencies of operation, such as radar and antenna devices as well as gyroscopic systems.

This book presents a time-delay approach to the analysis and synthesis of networked control systems (NCSs) under communication constraints. Differently from other approaches, the time-delay approach to NCSs allows communication delays to be larger than the sampling intervals in the presence of scheduling protocols. The book starts from a comprehensive introduction to three main approaches to sampled-data and networked control. It then focuses on time-delay approach, and the modelling of the closed-loop systems in the form of time-delay system. It presents discontinuous (in time) Lyapunov functional constructions that are efficient for NCSs in the presence of communications delays. Further, it highlights time-delay approaches developed to model and analyze NCSs under communication constraints, with a particular focus on dynamic quantization, round-robin, try-once-discard and stochastic protocols. The results are first presented for the continuous-time NCSs and then extended to discrete-time NCSs. Discussing recent developments in Lyapunov-based analysis of NCSs under communication constraints, the book is a valuable resource for researchers interested in sampled-data and networked control, and time-delay systems, as well as for graduate students in automatic control and systems theory.

Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of modelling accuracy they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it.

A further important component of machine intelligence is a kind of structural uniformity giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This learning ability is a key element of machine intelligence.

The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application.

Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems. "

This textbook teaches students techniques for the design of advanced digital systems using System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs). The author demonstrates design of custom hardware components for the FPGA fabric using VHDL, with implementation of custom hardware-software interfaces. Readers gain hands-on experience by writing programs and Linux device drivers in C to interact with custom hardware. This textbook enables laboratory experience in the design of custom digital systems using SoC FPGAs, emphasizing computational tasks such as digital signal processing, audio, or video processing.

Understanding the latest capabilities in the cyber threat landscape as well as the cyber forensic challenges and approaches is the best way users and organizations can prepare for potential negative events. Adopting an experiential learning approach, this book describes how cyber forensics researchers, educators and practitioners can keep pace with technological advances, and acquire the essential knowledge and skills, ranging from IoT forensics, malware analysis, and CCTV and cloud forensics to network forensics and financial investigations. Given the growing importance of incident response and cyber forensics in our digitalized society, this book will be of interest and relevance to researchers, educators and practitioners in the field, as well as students wanting to learn about cyber forensics.

No pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book's GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

This book introduces to blockchain and deep learning and explores and illustrates the current and new trends that integrate them. The pace and speeds for connectivity are certain on the ascend. Blockchain and deep learning are twin technologies that are integral to integrity and relevance of network contents. Since they are data-driven technologies, rapidly growing interests exist to incorporate them in efficient and secure data sharing and analysis applications. Blockchain and deep learning are sentinel contemporary research technologies. This book provides a comprehensive reference for blockchain and deep learning by covering all important topics. It identifies the bedrock principles and forward projecting methodologies that illuminate the trajectory of developments for the decades ahead.

The relay feedback test (RFT) has become a popular and efficient in process identification and automatic controller tuning. "Non-parametric Tuning of PID Controllers" couples new modifications of classical RFT with application-specific optimal tuning rules to form a non-parametric method of test-and-tuning. Test and tuning are coordinated through a set of common parameters so that a PID controller can obtain the desired gain or phase margins in a system exactly, even with unknown process dynamics. The concept of process-specific optimal tuning rules in the nonparametric setup, with corresponding tuning rules for flow, level pressure, and temperature control loops is presented in the text.

Common problems of tuning accuracy based on parametric and non-parametric approaches are addressed. In addition, the text treats the parametric approach to tuning based on the modified RFT approach and the exact model of oscillations in the system under test using the locus of a perturbedrelay system (LPRS) method. Industrial loop tuning for distributed control systems using modified RFT is also described. Many of the problems of tuning rules optimization and identification with modified RFT are accompanied by MATLAB(r) code, downloadable from http: //extras.springer.com/978-1-4471-4464-9 to allow the reader to duplicate the results.

"Non-parametric Tuning of PID Controllers" is written for readers with previous knowledge of linear control and will be of interest to academic control researchers and graduate students and to practitioners working in a variety of chemical- mechanical- and process-engineering-related industries.

This unique reference represents a cross-section of forefront robotics research, ranging from robotics and systems to learning, autonomy and failure detection, from vision and navigation to localization and mapping, which are based on the papers presented at the 1st European Robotics Symposium (EUROS-06) held in Palermo, Italy from 16-18 March, 2006. The European Robotics Symposium (EUROS) is a brand-new International scientific event promoted by EURON, the European Robotics Network.

Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.

This monograph examines the stability of various coupled systems with local Kelvin-Voigt damping. The development of this area is thoroughly reviewed along with the authors' contributions. New results are featured on the fundamental properties of solutions of linear transmission evolution PDEs involving Kelvin-Voigt damping, with special emphasis on the asymptotic behavior of these solutions. The vibrations of transmission problems are highlighted as well, making this a valuable resource for those studying this active area of research. The book begins with a brief description of the abstract theory of linear evolution equations with a particular focus on semigroup theory. Different types of stability are also introduced along with their connection to resolvent estimates. After this foundation is established, different models are presented for uni-dimensional and multi-dimensional linear transmission evolution partial differential equations with Kelvin-Voigt damping. Stabilization of Kelvin-Voigt Damped Systems will be a useful reference for researchers in mechanics, particularly those interested in the study of control theory of PDEs.

Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.

This intriguing book was born out of the many discussions the authors had in the past 10 years about the role of scale-free structure and dynamics in producing intelligent behavior in brains. The microscopic dynamics of neural networks is well described by the prevailing paradigm based in a narrow interpretation of the neuron doctrine. This book broadens the doctrine by incorporating the dynamics of neural fields, as first revealed by modeling with differential equations (K-sets). The book broadens that approach by application of random graph theory (neuropercolation). The book concludes with diverse commentaries that exemplify the wide range of mathematical/conceptual approaches to neural fields. This book is intended for researchers, postdocs, and graduate students, who see the limitations of network theory and seek a beachhead from which to embark on mesoscopic and macroscopic neurodynamics.

This book gathers together much of the author's work - both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes. In a very straightforward manner, the book introduces basic concepts to help readers follow the main ideas. By using variations of the NK model and including the concept of the Baldwin effect, the author presents new abstract models that are able to explain why sources of evolutionary innovation (genomes, symbiosis, sex, chromosomes, multicellularity) have been selected for and hence how complexity has increased over time in some lineages.

This book aims to provide the latest research developments and results in the domain of AI techniques for smart cyber ecosystems. It presents a holistic insight into AI-enabled theoretic approaches and methodology in IoT networking, security analytics using AI tools and network automation, which ultimately enable intelligent cyber space. This book will be a valuable resource for students, researchers, engineers and policy makers working in various areas related to cybersecurity and privacy for Smart Cities. This book includes chapters titled "An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security", "Smart City: Evolution and Fundamental Concepts", "Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment", "A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving Path to Eco-friendly Smart Cities", "A Novel Framework for a Cyber Secure Smart City", "Contemplating Security Challenges and Threats for Smart Cities", "Self-Monitoring Obfuscated IoT Network", "Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques", "Collaborative Digital Forensic Investigations Model for Law Enforcement: Oman as a Case Study", "Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review", "5G Security and the Internet of Things", "The Problem of Deepfake Videos and How to Counteract Them in Smart Cities", "The Rise of Ransomware Aided by Vulnerable IoT Devices", "Security Issues in Self-Driving Cars within Smart Cities", and "Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities". This book provides state-of-the-art research results and discusses current issues, challenges, solutions and recent trends related to security and organization within IoT and Smart Cities. We expect this book to be of significant importance not only to researchers and practitioners in academia, government agencies and industries, but also for policy makers and system managers. We anticipate this book to be a valuable resource for all those working in this new and exciting area, and a "must have" for all university libraries.

This book provides a coherent framework for understanding the essence of complex systems and the nature of digital transformations, analyzes challenges of and patterns in innovative development, and shares a wealth of insights and best practices, resulting in the most extensive coverage of the topic available. In particular, the book's cutting-edge contributions, prepared by scientists, engineers, and field experts,focus on the design, implementation, and evaluation of practical interventions that promote the innovative and sustainable development of complex systems. In addition to sharing a rich collection of cases from around the world, they provide a broad interdisciplinary analysis of collaboration mechanisms, theories and approaches to support and accelerate the development of complex systems.

This reference identifies information resources concerning virtual reality and provides detailed instruction on how to use these resources in an effective research strategy. Most of the chapters overview particular types of information sources, such as periodical and citation indexes, conference proceedings, technical reports, dissertations, and monographs. The chapters explain how to use these tools to gather information about virtual reality, and discussions of key resources are always placed in the larger context of information-gathering strategies specific to the field. Most of the resources are available in large public and academic libraries. The volume does not presuppose sophisticated technical knowledge of libraries, and it is written for the student and general researcher. The volume concludes with a set of algorithms that can be used to locate resources in the most typical searches, and a list of producers and publishers of related material.

This book provides a valuable reference for digital forensics practitioners and cyber security experts operating in various fields of law enforcement, incident response and commerce. It is also aimed at researchers seeking to obtain a more profound knowledge of Digital Forensics and Cybercrime. Furthermore, the book is an exceptional advanced text for PhD and Master degree programmes in Digital Forensics and Cyber Security. Each chapter of this book is written by an internationally-renowned expert who has extensive experience in law enforcement, industry and academia. The increasing popularity in the use of IoT devices for criminal activities means that there is a maturing discipline and industry around IoT forensics. As technology becomes cheaper and easier to deploy in an increased number of discrete, everyday objects, scope for the automated creation of personalised digital footprints becomes greater. Devices which are presently included within the Internet of Things (IoT) umbrella have a massive potential to enable and shape the way that humans interact and achieve objectives. These also forge a trail of data that can be used to triangulate and identify individuals and their actions. As such, interest and developments in autonomous vehicles, unmanned drones and 'smart' home appliances are creating unprecedented opportunities for the research communities to investigate the production and evaluation of evidence through the discipline of digital forensics.

This volume provides an introduction to and overview of the emerging field of interconnected networks which include multilayer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave - understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant - for example regarding diffusion, robustness and competition - the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

Focusses on filtering for linear processes, and helps design linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. This book defines various hierarchical classes of filtering problems based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties.

This book is a revision and extension of the author's 1995 Sourcebook of Control Systems Engineering. Because of the extensions and other modifications, it has been re-titled Handbook of Control Systems Engineering, which it is intended to be for its prime audience: advanced undergraduate students, beginning graduate students, and practicing engineers needing an understandable review of the field or recent developments which may prove useful. New in This Edition. Two new chapters on aspects of nonlinear systems have been incorporated. In the first of these, selected material for nonlinear systems is concentrated on four aspects: showing the value of certain linear controllers, arguing the suitability of algebraic linearization, reviewing the semi-classical methods of harmonic balance, and introducing the nonlinear change of variable technique known as feedback linearization. In the second new chapter, the topic of variable structure control, often with sliding mode, is introduced. A third chapter introduces discrete event systems, including several approaches to their analysis. The chapters on robust control and intelligent control have been extensively revised. Modest revisions and extensions have also been made to other chapters, often to incorporate extensions to nonlinear systems. Many references have been updated to more recent books, although old standards are still cited. Also, some of the advances in computer and communications technology are reflected. The index has been revised and expanded. The structure of the book is as in the first edition. Briefly, the aim is to present the topics in a fairly modular manner with certain main groupings. The first several chapters areconcerned with the hardware and software of the control task as well as systems engineering associated with the selection of appropriate components. The next chapters look at the sources and representations of the mathematical models used in the theory. A number of chapters then are concerned with standard classical or transform domain material as is usually presented in a first level university course, including stability theory, root locus diagrams, and Bode plots. The next group of chapters concerns the standard modern or state space material usually met in a second level course. Included here are observers, pole placement, and optimal control. Overlapping into usual graduate level courses are the next several chapters on more advanced optimal control, Kalman filtering, system identification, and standard adaptive control. The final chapters introduce more advanced, research level subjects. Here are selected topics in nonlinear control, intelligent control, robust control, and discrete event systems. The topics covered are intended to represent the mainstream of control systems teaching. Examples are presented to illustrate the computability of the theory presented. Handbook of Controls Systems Engineering, Second Edition is suitable as a secondary text for upper level undergraduate students, beginning graduate students, and as a reference for researchers and practitioners in industry.